Automatic Retrosynthetic Pathway Planning Using Template-free Models

@article{Lin2019AutomaticRP,
  title={Automatic Retrosynthetic Pathway Planning Using Template-free Models},
  author={Kangjie Lin and Youjun Xu and Jianfeng Pei and L. Lai},
  journal={arXiv: Quantitative Methods},
  year={2019}
}
We present an attention-based Transformer model for automatic retrosynthesis route planning. Our approach starts from reactants prediction of single-step organic reactions for given products, followed by Monte Carlo tree search-based automatic retrosynthetic pathway prediction. Trained on two datasets from the United States patent literature, our models achieved a top-1 prediction accuracy of over 54.6% and 63.0% with more than 95% and 99.6% validity rate of SMILES, respectively, which is the… Expand

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References

SHOWING 1-10 OF 42 REFERENCES
Computational Chemical Synthesis Analysis and Pathway Design
Computer-Assisted Retrosynthesis Based on Molecular Similarity
Route Designer: A Retrosynthetic Analysis Tool Utilizing Automated Retrosynthetic Rule Generation
Modelling Chemical Reasoning to Predict Reactions
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